Cohort profile: DNA methylation in the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA) – recruitment and participant characteristics
Bibliographic record
Abstract
PURPOSE: Epigenetic modifications including DNA methylation (DNAm) are proposed mechanisms by which social or environmental exposures may influence health and behaviours as we age. The Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA) DNAm cohort, established in 2013, is one of several worldwide, nationally representative prospective studies of ageing with biological samples from participants who consented to multiomic analysis. PARTICIPANTS: NICOLA recruited 8478 participants (8283 aged 50 years or older and 195 spouses or partners at the same address aged under 50 years). Computer-Assisted Personal Interviews, Self-Completion Questionnaires and detailed Health Assessments (HA) were completed. Of the 3471 (44.1%) participants who attended the HA in wave 1, which included venous blood sampling, 2000 were identified for the DNAm cohort. Following technical and data quality control checks, DNAm data are currently available for n=1870. FINDINGS TO DATE: There was no significant difference based on age, self-reported gender, education, employment, smoking or alcohol status and subjective health reports between the DNAm cohort and other HA attendees. Participants were more likely to be in the DNAm group if they lived with one other person (OR 1.26, 95% CI 1.07 to 1.49). The DNAm group had a lower proportion of depressed participants and those meeting criteria for post-traumatic stress disorder (11.7% and 4.4% vs 13.5% and 4.5%, respectively) categorised by objective assessment tools but this was not significant (OR 0.84, 95% CI 0.69 to 1.02 and OR 0.87, 95% CI 0.64 to 1.19). FUTURE PLANS: The deeply phenotyped DNAm cohort in NICOLA with planned prospective follow-up and additional multiomic data releases will increase the cohort's utility for research into ageing. The genomic and epigenetic data for the DNAm cohort has been deposited on the European Genome-Phenome Archive, increasing the profile of this cohort and data availability to researchers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".