Missense mutations in progranulin gene associated with frontotemporal lobar degeneration: study of pathogenetic features

NEUROBIOLOGY OF AGING

卷:38

Article

Karch, Celeste M.^1,2  Ezerskiy, Lubov¹  Redaelli, Veronica³  Giovagnoli, Anna Rita³  Tiraboschi, Pietro³  Pelliccioni, Giuseppe⁴  Pelliccioni, Paolo⁴  Kapetis, Dimos⁵  D'Amato, Ilaria³  Piccoli, Elena³  Ferretti, Maria Giulia³  Tagliavini, Fabrizio³  Rossi, Giacomina³ 

[1] Washington Univ, Sch Med, Dept Psychiat, St Louis, MO 63110 USA

[2] Washington Univ, Sch Med, Hope Ctr Program Prot Aggregat & Neurodegenerat, St Louis, MO USA

[3] Fdn IRCCS Ist Neurol Carlo Besta, Div Neurol & Neuropathol 5, Via Celoria 11, I-20133 Milan, Italy

[4] Geriatr Hosp, INRCA IRCCS, Div Neurol, Ancona, Italy

[5] Fdn IRCCS Ist Neurol Carlo Besta, Bioinformat Unit, Milan, Italy

关键词: Progranulin;    GRN;    Mutation;    Frontotemporal lobar degeneration;    Pathogenetic;    Functional analysis;   

DOI  :  10.1016/j.neurobiolaging.2015.10.029

来源: Elsevier

【 摘 要 】

GRN, the gene coding for the progranulin (PGRN) protein, was recognized as a gene linked to frontotemporal lobar degeneration (FTLD). The first mutations identified were null mutations giving rise to haploinsufficiency. Missense mutations were subsequently detected, but only a small subset has been functionally investigated. We identified missense mutations (C105Y, A199V, and R298H) in FTLD cases with family history and/or with low plasma PGRN levels. The aim of this study was to determine their pathogenicity. We performed functional studies, analyzing PGRN expression, secretion, and cleavage by elastase. GRN C105Y affected both secretion and elastase cleavage, likely representing a pathogenic mutation. GRN A199V did not alter the physiological properties of PGRN and GRN R298H produced only moderate effects on PGRN secretion, indicating that their pathogenicity is uncertain. In the absence of strong segregation data and neuropathological examinations, genetic, biomarker, and functional studies can be applied to an algorithm to assess the likelihood of pathogenicity for a mutation. This information can improve our understanding of the complex mechanisms by which GRN mutations lead to FTLD. (C) 2016 Elsevier Inc. All rights reserved.

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