Abstract 16819: Sequencing of Genetic Loci Associated With Leukocyte Telomere Length Reveals New Intronic Variants in African Americans
Bibliographic record
Abstract
Background: Shorter telomere length is associated with an increased risk of coronary artery disease (CAD). A prior genomewide association study (GWAS) on 37,684 European ancestry individuals identified seven loci determining leukocyte telomere length (LTL). A genetic risk score across all 7 loci showed an association with CAD. In this study we sequenced these loci to determine whether the same risk variants could be replicated in African admixed individuals. Methods: We used whole genome sequence data (WGS) in 127 healthy African American subjects from GeneSTAR, a family study of early-onset CAD. LTL was calculated from WGS raw bam data (>30x coverage on the Illumina HiSeq platform) for 7 contiguous repeats of the telomere motif (TTAGGG or CCCTAA, Ding et al., 2014). Tests for association for LTL adjusting for age and sex were performed for a total of 55,821 called variants from ~1Mb subset regions of WGS genotype data centered on each of the 7 European peak GWAS SNPs. Results: We identified a total of 17 variants with p<5x10 -4 mapping to 6 of the 7 regions examined; none of the prior European GWAS peak SNPs were significant. The peak SNP per region in the African Americans included intronic variants rs77138331 in ACYP2 (p=0.0005, MAF = 7%), rs149577640 in NAF1 (p=0.002, MAF=1%), rs35387865 in TERT (p=0.003, MAF = 1%) and rs186486116 in OBFC1 (p=0.004, MAF=1%). Additionally, novel intronic variants not previously observed in dbSNP located at chr19: 22190184 (p=0.005, MAF=1%) and chr2:62445438 (0.005, MAF=2%), mapping to ZNF208 and RTEL1 , were also identified as determinants of LTL. Discussion: This is the first study of telomere length in African Americans using a sequencing approach. We are unable to confirm the European-based GWAS variants but identify several associations mapping to genes of importance in telomere biology. Our results provide evidence that the set of SNPs to be included in calculation of a telomeric genetic CAD risk score may be different in populations of European and African ancestry.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 0.001 |
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".