دورية أكاديمية
أعرض في EDS

Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET.

التفاصيل البيبلوغرافية
العنوان: Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET.
المؤلفون: Corriveau-Lecavalier N; Department of Neurology, Mayo Clinic Rochester, USA; Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA., Barnard LR; Department of Neurology, Mayo Clinic Rochester, USA., Przybelski SA; Department of Quantitative Health Sciences, Mayo Clinic Rochester, USA., Gogineni V; Department of Neurology, Mayo Clinic Rochester, USA., Botha H; Department of Neurology, Mayo Clinic Rochester, USA., Graff-Radford J; Department of Neurology, Mayo Clinic Rochester, USA., Ramanan VK; Department of Neurology, Mayo Clinic Rochester, USA., Forsberg LK; Department of Neurology, Mayo Clinic Rochester, USA., Fields JA; Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA., Machulda MM; Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA., Rademakers R; Department of Neuroscience, Mayo Clinic Jacksonville, USA; VIB-UA Center for Molecular Neurology, VIB, University of Antwerp, Belgium., Gavrilova RH; Department of Medical Genetics, Mayo Clinic Rochester, USA., Lapid MI; Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA., Boeve BF; Department of Neurology, Mayo Clinic Rochester, USA., Knopman DS; Department of Neurology, Mayo Clinic Rochester, USA., Lowe VJ; Department of Radiology, Mayo Clinic Rochester, USA., Petersen RC; Department of Neurology, Mayo Clinic Rochester, USA., Jack CR; Department of Radiology, Mayo Clinic Rochester, USA., Kantarci K; Department of Radiology, Mayo Clinic Rochester, USA., Jones DT; Department of Neurology, Mayo Clinic Rochester, USA; Department of Radiology, Mayo Clinic Rochester, USA. Electronic address: jones.david@mayo.edu.
المصدر: NeuroImage. Clinical [Neuroimage Clin] 2024; Vol. 41, pp. 103559. Date of Electronic Publication: 2023 Dec 22.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101597070 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2213-1582 (Electronic) Linking ISSN: 22131582 NLM ISO Abbreviation: Neuroimage Clin Subsets: MEDLINE
أسماء مطبوعة: Original Publication: [Amsterdam] : Elsevier
مواضيع طبية MeSH: Frontotemporal Lobar Degeneration*/diagnostic imaging , Frontotemporal Lobar Degeneration*/genetics , Frontotemporal Dementia*/diagnostic imaging , Frontotemporal Dementia*/genetics, Humans ; Fluorodeoxyglucose F18 ; Intercellular Signaling Peptides and Proteins/genetics ; Progranulins/genetics ; Positron-Emission Tomography ; Mutation/genetics ; Phenotype
مستخلص: Genetic mutations causative of frontotemporal lobar degeneration (FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter-individual variability in their patterns of network degeneration and clinical manifestations. We collected clinical and 18 Fluorodeoxyglucose-positron emission tomography (FDG-PET) data from 39 patients with genetic FTLD, including 11 carrying the C9orf72 hexanucleotide expansion, 16 carrying a MAPT mutation and 12 carrying a GRN mutation. We performed a spectral covariance decomposition analysis between FDG-PET images to yield unbiased latent patterns reflective of whole brain patterns of metabolism ("eigenbrains" or EBs). We then conducted linear discriminant analyses (LDAs) to perform EB-based predictions of genetic mutation and predominant clinical phenotype (i.e., behavior/personality, language, asymptomatic). Five EBs were significant and explained 58.52 % of the covariance between FDG-PET images. EBs indicative of hypometabolism in left frontotemporal and temporo-parietal areas distinguished GRN mutation carriers from other genetic mutations and were associated with predominant language phenotypes. EBs indicative of hypometabolism in prefrontal and temporopolar areas with a right hemispheric predominance were mostly associated with predominant behavioral phenotypes and distinguished MAPT mutation carriers from other genetic mutations. The LDAs yielded accuracies of 79.5 % and 76.9 % in predicting genetic status and predominant clinical phenotype, respectively. A small number of EBs explained a high proportion of covariance in patterns of network degeneration across FTLD-related genetic mutations. These EBs contained biological information relevant to the variability in the pathophysiological and clinical aspects of genetic FTLD, and for offering valuable guidance in complex clinical decision-making, such as decisions related to genetic testing.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)
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فهرسة مساهمة: Keywords: Clinical neurology; FDG-PET; Frontotemporal dementia; Frontotemporal lobar degeneration; Machine learning
المشرفين على المادة: 0Z5B2CJX4D (Fluorodeoxyglucose F18)
0 (Intercellular Signaling Peptides and Proteins)
0 (Progranulins)
تواريخ الأحداث: Date Created: 20231226 Date Completed: 20240318 Latest Revision: 20240318
رمز التحديث: 20240318
مُعرف محوري في PubMed: PMC10944211
DOI: 10.1016/j.nicl.2023.103559
PMID: 38147792
قاعدة البيانات: MEDLINE
الوصف
تدمد:2213-1582
DOI:10.1016/j.nicl.2023.103559