Lymphoblastoid cell lines reveal associations of adult DNA methylation with childhood and current adversity that are distinct from whole blood associations
Bibliographic record
Abstract
BACKGROUND: Some cohort studies bank lymphoblastoid cell lines (LCLs) as a renewable source of participant DNA. However, although LCL DNA has proved valuable for genetic studies, its utility in epigenetic epidemiology research is unknown. METHODS: To assess whether LCL DNA can be used for life-course environmental epigenomics, we carried out a pilot methylomic study (using the Illumina Infinium Human Methylation 450 BeadChip) of nil-passage, Epstein-Barr virus (EBV)-transformed LCLs (n = 42) and 28 matched whole-blood (WB) samples. These were from adult male participants of the British 1958 birth cohort, selected for extremes of social economic position (SEP) in childhood and adulthood, with additional information available on childhood abuse and prenatal tobacco exposure. RESULTS: We identified a small number of weak associations between these exposures and methylation levels of both individual CpG sites and genomic regions in WB and LCLs. However, only one of the regional, and none of the individual CpG site associations were common to both sample types. The lack of overlap between the associations detected in LCL compared with those found in WB could either be due to the EBV-transformation process, or to the fact that, unlike WB, LCLs are essentially a single (CD19+) cell type. We provide evidence that the latter is the more potent explanation, by showing that CpG sites known to be differentially methylated between different types of blood cell have significantly lower correlations (R = 0.11) than average (R = 0.2) between WB and LCLs in our datasets, whereas sites known to be affected by EBV-transformation have significantly higher correlations (R = 0.3). CONCLUSIONS: This small pilot study suggests that the DNA methylation profile of LCLs is more closely related to that of B cells than WB and, additionally, that LCLs may nevertheless be useful for life-course environmental epigenomics.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 0.001 |
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".