MétaCan
Menu
← Back to cohort
Record W4403908157 · doi:10.1101/2024.10.28.24316295

Multidimensional Epigenetic Clocks Reveal Physiological System-Specific Aging in Schizophrenia

2024· preprint· en· W4403908157 on OpenAlexaff
Zachary M. Harvanek, Raghav Sehgal, Daniel S. Borrus, Jessica Kasamoto, Ryan Smith, Michael J. Corley, Christiaan H. Vinkers, Marco P. Boks, Varun B. Dwaraka, Jessica Lasky‐Su, Albert Higgins‐Chen

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsCytodiagnostics (Canada)
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Meta-analysisEpigeneticsPsychologyComputer scienceCognitive psychologyNeuroscienceBiologyMedicinePsychiatryGeneticsInternal medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: Schizophrenia is associated with increased age-related morbidity, mortality, and frailty, which are not entirely explained by behavioral factors. Prior studies using epigenetic clocks have suggested that schizophrenia is associated with accelerated aging, however these studies have primarily used unidimensional clocks that summarize aging as a single "biological age" score. OBJECTIVE: This meta-analysis uses multidimensional epigenetic clocks that split aging into multiple scores to analyze biological aging in schizophrenia. These novel clocks may provide more granular insights into the mechanistic relationships between schizophrenia, epigenetic aging, and premature morbidity and mortality. STUDY SELECTION: Selected studies included patients with schizophrenia-spectrum disorders and non- psychiatric controls with available DNA methylation data. Seven cross-sectional datasets were available for this study, with a total sample size of 1,891 patients with schizophrenia and 1,881 controls. DATA EXTRACTION AND SYNTHESIS: Studies were selected by consensus Meta-analyses were performed using fixed-effect models. MAIN OUTCOMES AND MEASURES: We analyzed multidimensional epigenetic clocks, including causality- enriched CausAge clocks, physiological system-specific SystemsAge clocks, RetroelementAge, DNAmEMRAge, and multi omics-informed OMICmAge. Meta-analyses examined clock associations with schizophrenia disease status and clozapine use, after accounting for age and sex. RESULTS: Overall SystemsAge, CausAge, DNAmEMRAge, and OMICmAge scores demonstrated increased epigenetic aging in patients with schizophrenia after strict multiple-comparison testing. Ten of the eleven SystemsAge sub-clocks corresponding to different physiological systems demonstrated increased aging, with strongest effects for Heart and Lung followed by Metabolic and Brain systems. The causality- enriched clocks indicated increases in both damaging and adaptive aging, though these effects were weaker compared to SystemsAge scores. OMICmAge indicated changes in multiple clinical biomarkers, including hematologic and hepatic markers that support system-specific aging, as well as novel proteins and metabolites not previously linked to schizophrenia. Most clocks demonstrated age acceleration at the first psychotic episode. Notably, clozapine use was associated with increased Heart and Inflammation aging, which may partially be driven by smoking. Most results survived strict Bonferroni multiple testing correction. CONCLUSIONS AND RELEVANCE: These are the first analyses of novel multidimensional clocks in patients with schizophrenia and provide a nuanced view of aging that identifies multiple organ systems at high risk for disease in schizophrenia-related disorders.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.011
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.272
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuemedRxiv→Same topicEpigenetics and DNA Methylation→French-language works237,207→