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Record W2900305568 · doi:10.1093/geroni/igy023.232

BROAD-SCALE, MULTI-SYSTEM DYSREGULATION OF GENE EXPRESSION: TOWARD CLINICAL QUANTIFICATION OF AGING

2018· article· en· W2900305568 on OpenAlexaff
Alan A. Cohen, Fabien Dufour, Pierre‐Étienne Jacques

Bibliographic record

VenueInnovation in Aging · 2018
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBiologyGene expressionGeneComputational biologyKEGGProteostasisSystems biologyFunction (biology)microRNABiological pathwayBioinformaticsGeneticsGene ontology

Abstract

fetched live from OpenAlex

Our previous work on clinical blood biomarkers established statistical distance as a proxy for dysregulation from homeostatic norms. Here, we expand this approach to gene expression data, permitting the definition of many more systems at a finer biological scale. We conducted secondary data analysis with 880 whole-blood gene expression profiles from the Rotterdam Study. Systems were defined using Gene Ontology annotations. For each system, we calculated the correlation between Mahalanobis distance and age. Among 13,189 systems tested, 1029 showed evidence of age-related increases in dysregulation, substantially more than the 660 expected by chance. Furthermore, these systems were highly clustered, with a strong representation of systems related to immune cell function, renal function, protein localization and maintenance of proteostasis, ribosomal RNA metabolism and regulation of signaling pathways, such as the MAP kinase pathway or cell cycle phase transition pathways. These results imply the potential to develop fine-scale metrics of aging for clinical use.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.124
GPT teacher head0.409
Teacher spread0.285 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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