A high-density SNP genome-wide linkage search of 206 families identifies susceptibility loci for chronic lymphocytic leukemia
Bibliographic record
Abstract
Chronic lymphocytic leukemia (CLL) and other B-cell lymphoproliferative disorders display familial aggregation. To identify a susceptibility gene for CLL, we assembled families from the major European (ICLLC) and American (GEC) consortia to conduct a genome-wide linkage analysis of 101 new CLL pedigrees using a high-density single nucleotide polymorphism (SNP) array and combined the results with data from our previously reported analysis of 105 families. Here, we report on the combined analysis of the 206 families. Multipoint linkage analyses were undertaken using both nonparametric (model-free) and parametric (model-based) methods. After the removal of high linkage disequilibrium SNPs, we obtained a maximum nonparametric linkage (NPL) score of 3.02 (P = .001) on chromosome 2q21.2. The same genomic position also yielded the highest multipoint heterogeneity LOD (HLOD) score under a common recessive model of disease susceptibility (HLOD = 3.11; P = 7.7 x 10(-5)), which was significant at the genome-wide level. In addition, 2 other chromosomal positions, 6p22.1 (corresponding to the major histocompatibility locus) and 18q21.1, displayed HLOD scores higher than 2.1 (P < .002). None of the regions coincided with areas of common chromosomal abnormalities frequently observed in CLL. These findings provide direct evidence for Mendelian predisposition to CLL and evidence for the location of disease loci.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".