Differential genetic influences over colorectal cancer risk and gene expression in large bowel mucosa
Bibliographic record
Abstract
Abstract Site‐specific variation in colorectal cancer (CRC) incidence, biology and prognosis are poorly understood. We sought to determine whether common genetic variants influencing CRC risk might exhibit topographical differences on CRC risk through regional differences in effects on gene expression in the large bowel mucosa. We conducted a site‐specific genetic association study (10 630 cases, 31 331 controls) to identify whether established risk variants exert differential effects on risk of proximal, compared to distal CRC. We collected normal colorectal mucosa and blood from 481 subjects and assessed mucosal gene expression using Illumina HumanHT‐12v4 arrays in relation to germline genotype. Expression quantitative trait loci (eQTLs) were explored by anatomical location of sampling. The rs3087967 genotype (chr11q23.1 risk variant) exhibited significant site‐specific effects—risk of distal CRC (odds ratio [OR] = 1.20,P = 8.20 × 10−20) with negligible effects on proximal CRC risk (OR = 1.05,P = .10). Expression of 1261 genes differed between proximal and distal colonic mucosa (top hitPRACgene, fold‐difference = 10,P = 3.48 × 10−57). In eQTL studies, rs3087967 genotype was associated with expression of 8 cis‐ and 21 trans‐genes. Four of these (AKAP14,ADH5P4,ASGR2,RP11‐342M1.7) showed differential effects by site, with strongest trans‐eQTL signals in proximal colonic mucosa (eg,AKAP14, beta = 0.61,P = 5.02 × 10−5) and opposite signals in distal mucosa (AKAP14, beta = −0.17,P = .04). In summary, genetic variation at the chr11q23.1 risk locus imparts greater risk of distal rather than proximal CRC and exhibits site‐specific differences in eQTL effects in normal mucosa. Topographical differences in genomic control over gene expression relevant to CRC risk may underlie site‐specific variation in CRC. Results may inform individualised CRC screening programmes.
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 | 0.000 | 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".