Literature DB >> 29653316

Clinical variability and onset age modifiers in an extended Belgian GRN founder family.

Eline Wauters1, Sara Van Mossevelde2, Kristel Sleegers1, Julie van der Zee1, Sebastiaan Engelborghs3, Anne Sieben4, Rik Vandenberghe5, Stéphanie Philtjens1, Marleen Van den Broeck1, Karin Peeters1, Ivy Cuijt1, Wouter De Coster1, Tim Van Langenhove6, Patrick Santens6, Adrian Ivanoiu7, Patrick Cras8, Jan L De Bleecker6, Jan Versijpt9, Roeland Crols10, Nina De Klippel11, Jean-Jacques Martin12, Peter P De Deyn13, Marc Cruts1, Christine Van Broeckhoven14.   

Abstract

We previously reported a granulin (GRN) null mutation, originating from a common founder, in multiple Belgian families with frontotemporal dementia. Here, we used data of a 10-year follow-up study to describe in detail the clinical heterogeneity observed in this extended founder pedigree. We identified 85 patients and 40 unaffected mutation carriers, belonging to 29 branches of the founder pedigree. Most patients (74.4%) were diagnosed with frontotemporal dementia, while others had a clinical diagnosis of unspecified dementia, Alzheimer's dementia or Parkinson's disease. The observed clinical heterogeneity can guide clinical diagnosis, genetic testing, and counseling of mutation carriers. Onset of initial symptomatology is highly variable, ranging from age 45 to 80 years. Analysis of known modifiers, suggested effects of GRN rs5848, microtubule-associated protein tau H1/H2, and chromosome 9 open reading frame 72 G4C2 repeat length on onset age but explained only a minor fraction of the variability. Contrary, the extended GRN founder family is a valuable source for identifying other onset age modifiers based on exome or genome sequences. These modifiers might be interesting targets for developing disease-modifying therapies.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Clinical heterogeneity; Founder pedigree; Frontotemporal dementia; GRN; Modifiers

Mesh:

Substances:

Year:  2018        PMID: 29653316     DOI: 10.1016/j.neurobiolaging.2018.03.007

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  5 in total

Review 1.  Applications of machine learning to diagnosis and treatment of neurodegenerative diseases.

Authors:  Monika A Myszczynska; Poojitha N Ojamies; Alix M B Lacoste; Daniel Neil; Amir Saffari; Richard Mead; Guillaume M Hautbergue; Joanna D Holbrook; Laura Ferraiuolo
Journal:  Nat Rev Neurol       Date:  2020-07-15       Impact factor: 42.937

2.  The Use of Biomarkers and Genetic Screening to Diagnose Frontotemporal Dementia: Evidence and Clinical Implications.

Authors:  Helena Gossye; Christine Van Broeckhoven; Sebastiaan Engelborghs
Journal:  Front Neurosci       Date:  2019-08-06       Impact factor: 4.677

3.  Impaired β-glucocerebrosidase activity and processing in frontotemporal dementia due to progranulin mutations.

Authors:  Andrew E Arrant; Jonathan R Roth; Nicholas R Boyle; Shreya N Kashyap; Madelyn Q Hoffmann; Charles F Murchison; Eliana Marisa Ramos; Alissa L Nana; Salvatore Spina; Lea T Grinberg; Bruce L Miller; William W Seeley; Erik D Roberson
Journal:  Acta Neuropathol Commun       Date:  2019-12-23       Impact factor: 7.801

4.  NanoSatellite: accurate characterization of expanded tandem repeat length and sequence through whole genome long-read sequencing on PromethION.

Authors:  Arne De Roeck; Wouter De Coster; Liene Bossaerts; Rita Cacace; Tim De Pooter; Jasper Van Dongen; Svenn D'Hert; Peter De Rijk; Mojca Strazisar; Christine Van Broeckhoven; Kristel Sleegers
Journal:  Genome Biol       Date:  2019-11-14       Impact factor: 13.583

Review 5.  Emerging genetic complexity and rare genetic variants in neurodegenerative brain diseases.

Authors:  Federica Perrone; Rita Cacace; Julie van der Zee; Christine Van Broeckhoven
Journal:  Genome Med       Date:  2021-04-14       Impact factor: 11.117

  5 in total

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