A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci
Bibliographic record
Abstract
Abstract Background: Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. Methods: We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results: We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry–European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10−7) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact: A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609–18. ©2016 AACR.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.014 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".