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Record W2949280410 · doi:10.1038/s41467-018-08279-3

Neuropathological correlates and genetic architecture of microglial activation in elderly human brain

2019· article· en· W2949280410 on OpenAlexfundno aff
Daniel Felsky, Tina Roostaei, Kwangsik Nho, Shannon L. Risacher, Elizabeth M. Bradshaw, Vladislav Petyuk, Julie A. Schneider, Andrew J. Saykin, David A. Bennett, Philip L. De Jager

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeU.S. National Library of MedicineNational Institute on AgingTranslational Genomics Research InstituteNational Institutes of HealthCanadian Institutes of Health ResearchIllinois Department of Public Health
KeywordsMicrogliaNeuropathologyNeuroinflammationNeuroscienceHuman brainDementiaCognitive declineNeurodegenerationDiseaseAmyloid (mycology)BiologyApolipoprotein EAlzheimer's diseaseGenetic architectureMedicineInflammationPathologyPhenotypeGeneticsGeneImmunology

Abstract

fetched live from OpenAlex

Abstract Microglia, the resident immune cells of the brain, have important roles in brain health. However, little is known about the regulation and consequences of microglial activation in the aging human brain. Here we report that the proportion of morphologically activated microglia (PAM) in postmortem cortical tissue is strongly associated with β-amyloid, tau-related neuropathology, and the rate of cognitive decline. Effect sizes for PAM measures are substantial, comparable to that of APOE ε4, the strongest genetic risk factor for Alzheimer’s disease, and mediation models support an upstream role for microglial activation in Alzheimer’s disease via accumulation of tau. Further, we identify a common variant (rs2997325) influencing PAM that also affects in vivo microglial activation measured by [ 11 C]-PBR28 PET in an independent cohort. Thus, our analyses begin to uncover pathways regulating resident neuroinflammation and identify overlaps of PAM’s genetic architecture with those of Alzheimer’s disease and several other traits.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.287
Teacher spread0.263 · 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 designBench or experimental
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

Citations172
Published2019
Admission routes1
Has abstractyes

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