Extremely Low Birth Weight and Accelerated Biological Aging
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Extremely low birth weight (ELBW) (<1000 g) survivors are exposed to elevated levels of physiologic stress during their lives and may be susceptible to accelerated aging. Using the oldest known longitudinally followed cohort of ELBW survivors, we compared biological aging in this group using an epigenetic clock to a sample of matched normal birth weight (NBW) (>2500 g) control participants. METHODS: Buccal cells were collected from 45 ELBW survivors and 49 NBW control participants at 30 to 35 years of age. Epigenetic age was calculated from the weighted average of DNA methylation at 353 cytosine-phosphate-guanine sequence within DNA sites, by using the Illumina Infinium Human Methylation EPIC 850k BeadChip array. RESULTS: Before and after statistically adjusting for neurosensory impairment and the presence of chronic health conditions, a significant sex by birth weight group interaction was observed in the 353-site epigenetic-clock assay (P = .03), whereby ELBW men had a significantly older epigenetic age than NBW men (4.6 years; P = .01). Women born at ELBW were not found to be epigenetically older than their NBW peers. CONCLUSIONS: The results of this study suggest that prenatal exposures may play an important role in aging, and that men born preterm may experience accelerated aging relative to their peers. We further highlight the need to monitor and promote the health of preterm survivors, with a particular focus on healthy aging across the life span.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".