A Genome-Wide Association Study of Chronic Obstructive Pulmonary Disease in Hispanics
Bibliographic record
Abstract
RATIONALE: Genome-wide association studies (GWAS) of chronic obstructive pulmonary disease (COPD) have identified disease-susceptibility loci, mostly in subjects of European descent. OBJECTIVES: We hypothesized that by studying Hispanic populations we would be able to identify unique loci that contribute to COPD pathogenesis in Hispanics but remain undetected in GWAS of non-Hispanic populations. METHODS: We conducted a metaanalysis of two GWAS of COPD in independent cohorts of Hispanics in Costa Rica and the United States (Multi-Ethnic Study of Atherosclerosis [MESA]). We performed a replication study of the top single-nucleotide polymorphisms in an independent Hispanic cohort in New Mexico (the Lovelace Smokers Cohort). We also attempted to replicate prior findings from genome-wide studies in non-Hispanic populations in Hispanic cohorts. MEASUREMENTS AND MAIN RESULTS: We found no genome-wide significant association with COPD in our metaanalysis of Costa Rica and MESA. After combining the top results from this metaanalysis with those from our replication study in the Lovelace Smokers Cohort, we identified two single-nucleotide polymorphisms approaching genome-wide significance for an association with COPD. The first (rs858249, combined P value = 6.1 × 10(-8)) is near the genes KLHL7 and NUPL2 on chromosome 7. The second (rs286499, combined P value = 8.4 × 10(-8)) is located in an intron of DLG2. The two most significant single-nucleotide polymorphisms in FAM13A from a previous genome-wide study in non-Hispanics were associated with COPD in Hispanics. CONCLUSIONS: We have identified two novel loci (in or near the genes KLHL7/NUPL2 and DLG2) that may play a role in COPD pathogenesis in Hispanic populations.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".