Epigenome-wide analysis of sperm cells identifies IL22 as a possible germ line risk locus for psoriatic arthritis
Bibliographic record
Abstract
Psoriasis and its associated inflammatory arthritis, psoriatic arthritis (PsA), have a clear heritable component, but a large proportion of the heritable risk remains unexplained by gene sequence variation. This study aimed to determine if epigenetic factors contribute to the missing heritability in psoriatic disease. DNA methylation profiling was performed on sperm cells from 23 probands with psoriasis without PsA (PsC), 13 PsA probands, and 18 unaffected controls. Differentially methylated CpGs and regions (DMRs) were identified and validated by pyrosequencing. Underlying AluY and copy number variation (CNV) in the HCG26 and IL22 genes, respectively, were assessed by genotyping. Array, subject's age, age of psoriasis onset, psoriasis severity, and medication usage were found to influence methylation at many genes and were included as covariates in the analysis. Between PsC probands vs. controls, 169 DMRs were found; 754 DMRs were found between PsA probands vs. controls, and 86 between PsA and PsC probands (adjusted p<0.05). Differences in methylation across DMRs were generally subtle (<10%) but correlated well with pyrosequencing. Biological inference prioritized notable DMRs associated with skin disease (SIGLEC14, JAM3, PCOLCE, RXRB), skin and/or joint disease (MBP, OSBPL5, SNORD115, HCG26), and joint disease (IL22, ELF5, PPP2R2D, PTPRN2, HCG26). Hypermethylation of the DMR within the first exon of arthritis-associated IL22 showed significant correlation (rho = 0.34, 95% CI 0.06-0.57, p = 0.01) between paired sperm and blood samples, independent of a CNV within the same region. Further studies are needed to rule out underlying genetic causes and determine if these represent heritable, constitutional epimutations, or are the result of exposure of germ cells to endogenous or exogenous environmental factors.
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 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) | 0.002 | 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 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".