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Progranulin plasma levels predict the presence of GRN mutations in asymptomatic subjects and do not correlate with brain atrophy: results from the GENFI study

2017· article· en· W2770087407 on OpenAlexaff
Daniela Galimberti, Giorgio Fumagalli, Chiara Fenoglio, Sara Cioffi, Andrea Arighi, María Serpente, Barbara Borroni, Alessandro Padovani, Fabrizio Tagliavini, Mario Masellis, Maria Carmela Tartaglia, John C. van Swieten, Lieke Meeter, Caroline Graff, Alexandre de Mendonça, Martina Bocchetta, Jonathan D. Rohrer, Elio Scarpini, Christin Andersson, Silvana Archetti, Luisa Benussi, Giuliano Binetti, Sandra E. Black, David M. Cash, Maura Cosseddu, Katrina M. Dick, Marie Fallström, Carlos Ferreira, Elizabeth Finger, Nick C. Fox, Morris Freedman, Giovanni B. Frisoni, Stefano Gazzina, Roberta Ghidoni, Marina Grisoli, Vesna Jelić, Lize C. Jiskoot, Ron Keren, Robert Laforce, Gemma Lombardi, Carolina Maruta, Simon Mead, Rick van Minkelen, Benedetta Nacmias, Linn Öijerstedt, Sébastien Ourselin, Jessica Panman, Michela Pievani, Cristina Polito, Sara Prioni, Rosa Rademakers, Veronica Redaelli, Ekaterina Rogaeva, Giacomina Rossi, C. Besta, Martin N. Rossor, James B. Rowe, Sandro Sorbi, David F. Tang‐Wai, David L. Thomas, Håkan Thonberg, Pietro Tiraboschi, Ana Verdelho, Jason D. Warren

Bibliographic record

VenueNeurobiology of Aging · 2017
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Institute of Neurological Disorders and StrokeMinistero della SaluteMedical Research CouncilNational Institute for Health and Care ResearchWellcome Trust
KeywordsAsymptomaticAtrophyInternal medicineFrontotemporal dementiaMedicineGenotypeDementiaPathologyGastroenterologyEndocrinologyGeneBiologyGeneticsDisease

Abstract

fetched live from OpenAlex

We investigated whether progranulin plasma levels are predictors of the presence of progranulin gene (GRN) null mutations or of the development of symptoms in asymptomatic at risk members participating in the Genetic Frontotemporal Dementia Initiative, including 19 patients, 64 asymptomatic carriers, and 77 noncarriers. In addition, we evaluated a possible role of TMEM106B rs1990622 as a genetic modifier and correlated progranulin plasma levels and gray-matter atrophy. Plasma progranulin mean ± SD plasma levels in patients and asymptomatic carriers were significantly decreased compared with noncarriers (30.5 ± 13.0 and 27.7 ± 7.5 versus 99.6 ± 24.8 ng/mL, p < 0.00001). Considering the threshold of >61.55 ng/mL, the test had a sensitivity of 98.8% and a specificity of 97.5% in predicting the presence of a mutation, independent of symptoms. No correlations were found between progranulin plasma levels and age, years from average age at onset in each family, or TMEM106B rs1990622 genotype (p > 0.05). Plasma progranulin levels did not correlate with brain atrophy. Plasma progranulin levels predict the presence of GRN null mutations independent of proximity to symptoms and brain atrophy.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
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 score0.036
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.040
GPT teacher head0.307
Teacher spread0.267 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations58
Published2017
Admission routes1
Has abstractyes

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