Faculty Opinions recommendation of Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease.
Bibliographic record
Abstract
More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10(-16), odds ratio ≈ 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models. PMID: 21983784 Funding information This work was supported by: NIAID NIH HHS, United States Grant ID: U19 AI067152 Medical Research Council, United Kingdom Grant ID: G0600329 NCRR NIH HHS, United States Grant ID: M01 RR000425-30S1 NIDDK NIH HHS, United States Grant ID: U01 DK062431 NIDDK NIH HHS, United States Grant ID: U01 DK062432-01 NIDDK NIH HHS, United States Grant ID: U01 DK062420 NIDDK NIH HHS, United States Grant ID: DK062413 NIDDK NIH HHS, United States Grant ID: DK062432 Medical Research Council, United Kingdom Grant ID: G0800675 NIDDK NIH HHS, United States Grant ID: R01 DK083756 NIDDK NIH HHS, United States Grant ID: P01 DK046763 NIDDK NIH HHS, United States Grant ID: DK086502 NIDDK NIH HHS, United States Grant ID: P01-DK046763 NIDDK NIH HHS, United States Grant ID: DK062429 NIDDK NIH HHS, United States Grant ID: U01 DK062423 NIDDK NIH HHS, United States Grant ID: U01 DK062431-01 NIDDK NIH HHS, United States Grant ID: DK063491 NIDDK NIH HHS, United States Grant ID: R01 DK083756-01 NIDDK NIH HHS, United States Grant ID: P30 DK043351-21 NIDDK NIH HHS, United States Grant ID: U01-DK062413 NIDDK NIH HHS, United States Grant ID: R21-DK84554-01 NIDDK NIH HHS, United States Grant ID: DK062420 NIAID NIH HHS, United States Grant ID: R01 AI062773 NCRR NIH HHS, United States Grant ID: M01 RR000425 NIDDK NIH HHS, United States Grant ID: U01 DK062420-06 NIDDK NIH HHS, United States Grant ID: DK060049 NIAID NIH HHS, United States Grant ID: R01 AI062773-01A1 NIAID NIH HHS, United States Grant ID: P01 AI065687 NIDDK NIH HHS, United States Grant ID: DK062431 Chief Scientist Office, United Kingdom Grant ID: CZB/4/540 NIDDK NIH HHS, United States Grant ID: U01 DK062422-01 Chief Scientist Office, United Kingdom Grant ID: ETM/75 NIDDK NIH HHS, United States Grant ID: P30 DK043351-18 NIDDK NIH HHS, United States Grant ID: DK83756 NIAID NIH HHS, United States Grant ID: AI065687 NIDDK NIH HHS, United States Grant ID: U01 DK062422 NIDDK NIH HHS, United States Grant ID: U01 DK062429-01 NIDDK NIH HHS, United States Grant ID: P30 DK063491 NIDDK NIH HHS, United States Grant ID: U01 DK062429 NIDDK NIH HHS, United States Grant ID: R01 DK060049-08 NIDDK NIH HHS, United States Grant ID: U01 DK062423-01 NIDDK NIH HHS, United States Grant ID: R01 DK064869 NIDDK NIH HHS, United States Grant ID: U01 DK062432 NIDDK NIH HHS, United States Grant ID: R01 DK064869-01 NIAID NIH HHS, United States Grant ID: AI067152 Canadian Institutes of Health Research, Canada Grant ID: 01038 NIDDK NIH HHS, United States Grant ID: DK062423 NIDDK NIH HHS, United States Grant ID: P30 DK063491-06 NIDDK NIH HHS, United States Grant ID: DK064869 NIDDK NIH HHS, United States Grant ID: RC1 DK086502-01 NIDDK NIH HHS, United States Grant ID: R21 DK084554 NIDDK NIH HHS, United States Grant ID: R21 DK084554-01 NIDDK NIH HHS, United States Grant ID: P30 DK043351 NHGRI NIH HHS, United States Grant ID: U01 HG005923 NIDDK NIH HHS, United States Grant ID: U01 DK062413 NIDDK NIH HHS, United States Grant ID: DK062422 NHGRI NIH HHS, United States Grant ID: U54 HG003067 NIDDK NIH HHS, United States Grant ID: R01 DK060049 NIDDK NIH HHS, United States Grant ID: U01 DK062413-08 NHGRI NIH HHS, United States Grant ID: HG005923 NIDDK NIH HHS, United States Grant ID: U01 DK062432-07 NHGRI NIH HHS, United States Grant ID: U01 HG005923-01 NIDDK NIH HHS, United States Grant ID: RC1 DK086502 NIDDK NIH HHS, United States Grant ID: DK043351 NHGRI NIH HHS, United States Grant ID: U54 HG003067-01 NIAID NIH HHS, United States Grant ID: AI062773 NIDDK NIH HHS, United States Grant ID: P01 DK046763-08 NCRR NIH HHS, United States Grant ID: M01-RR00425 More Less keyboard_arrow_down
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 | 0.009 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.510 | 0.310 |
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".