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Record W3081060264 · doi:10.1093/braincomms/fcaa122

Analysis of brain atrophy and local gene expression in genetic frontotemporal dementia

2020· article· en· W3081060264 on OpenAlex
André Altmann, David M. Cash, Martina Bocchetta, Carolin Heller, Regina H. Reynolds, Katrina Moore, Rhian S. Convery, David L. Thomas, John C. van Swieten, Fermín Moreno, Raquel Sánchez‐Valle, Barbara Borroni, Robert Laforce, Mario Masellis, Maria Carmela Tartaglia, Caroline Graff, Daniela Galimberti, James B. Rowe, Elizabeth Finger, Matthis Synofzik, Rik Vandenberghe, Alexandre de Mendonça, Fabrizio Tagliavini, Isabel Santana, Simon Ducharme, Christopher Butler, Alexander Gerhard, Johannes Levin, Adrian Danek, Giovanni B. Frisoni, Roberta Ghidoni, Sandro Sorbi, Markus Otto, Mina Ryten, Jonathan D. Rohrer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrain Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill UniversityWestern UniversityMontreal Neurological Institute and HospitalUniversity of TorontoOccupational Cancer Research CentreHealth Sciences CentreMcGill University Health CentreSunnybrook Health Science CentreUniversité Laval
FundersMedical Research CouncilMinistero della SaluteEuropean CommissionAlzheimer's SocietyBrain Research TrustWolfson FoundationNational Institute for Health and Care Research
KeywordsC9orf72Frontotemporal dementiaAtrophyBiologyFrontotemporal lobar degenerationGeneticsGeneDementiaNeurosciencePathologyMedicineDisease

Abstract

fetched live from OpenAlex

Abstract Frontotemporal dementia is a heterogeneous neurodegenerative disorder characterized by neuronal loss in the frontal and temporal lobes. Despite progress in understanding which genes are associated with the aetiology of frontotemporal dementia, the biological basis of how mutations in these genes lead to cell loss in specific cortical regions remains unclear. In this work, we combined gene expression data for 16 772 genes from the Allen Institute for Brain Science atlas with brain maps of grey matter atrophy in symptomatic C9orf72, GRN and MAPT mutation carriers obtained from the Genetic Frontotemporal dementia Initiative study. No significant association was seen between C9orf72, GRN and MAPT expression and the atrophy patterns in the respective genetic groups. After adjusting for spatial autocorrelation, between 1000 and 5000 genes showed a negative or positive association with the atrophy pattern within each individual genetic group, with the most significantly associated genes being TREM2, SSBP3 and GPR158 (negative association in C9Orf72, GRN and MAPT respectively) and RELN, MXRA8 and LPA (positive association in C9Orf72, GRN and MAPT respectively). An overrepresentation analysis identified a negative association with genes involved in mitochondrial function, and a positive association with genes involved in vascular and glial cell function in each of the genetic groups. A set of 423 and 700 genes showed significant positive and negative association, respectively, with atrophy patterns in all three maps. The gene set with increased expression in spared cortical regions was enriched for neuronal and microglial genes, while the gene set with increased expression in atrophied regions was enriched for astrocyte and endothelial cell genes. Our analysis suggests that these cell types may play a more active role in the onset of neurodegeneration in frontotemporal dementia than previously assumed, and in the case of the positively associated cell marker genes, potentially through emergence of neurotoxic astrocytes and alteration in the blood–brain barrier, respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.340
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it