Abstract 2835: Mitochondrial genetic variants influence ovarian cancer risk
Bibliographic record
Abstract
Abstract Mitochondria have been implicated in carcinogenesis because of their central role in apoptosis, free radical production, and cellular energy metabolism. Although studies have identified somatic mitochondrial DNA mutations in ovarian cancers, little attention has been directed to the possible role of germline mitochondrial variants in mitochondrial dysfunction and subsequent ovarian cancer development. Through an ongoing epithelial ovarian cancer genome-wide association study of 1,856 invasive cases (59% with serous carcinomas) and 1,912 controls (frequency-matched on age, race, and study site), we genotyped 138 SNPs tagging variation in the maternally-inherited mitochondrial genome (mtDNA) to evaluate the hypothesis that single nucleotide polymorphisms (SNPs) in mtDNA are associated with ovarian cancer risk. All subjects were non-Hispanic, non-Jewish Caucasians, and were genotyped with the Illumina 610-quad Beadchip. Samples and SNPs with call rates less than 95% were excluded. Subjects with ambiguous gender, unresolved identical genotypes, and less than 80% European ancestry were excluded. For each SNP, logistic regression was used to estimate odds ratios (OR) and corresponding 95% confidence intervals (CI) between carriers of the minor versus major maternally-inherited allele and case status. Subgroup analysis was conducted to estimate allele-specific risks between serous-only cases and controls. Haplotype analysis was performed for regions containing statistically significant SNPs (p<0.05). Two rare SNPs, C16329T in the displacement loop gene (MT-D-loop) (OR: 6.72, 95%CI: 1.5-29.8, p=0.004; minor allele frequency (MAF)=0.001) and C15905T in the tRNA threonine gene (MT-TT) (OR: 1.60, 95%CI: 1.1-2.3, p=0.009; MAF=0.027), were associated with increased ovarian cancer risk; whereas T6777C in the cytochrome c oxidase subunit 1 gene (MT-CO1) (OR: 0.68, 95%CI: 0.51-0.91, p=0.009; MAF=0.063) was associated with decreased risk. All three SNPs remained statistically significant after adjustment for multiple comparisons within the mitochondrial SNPs using permutation testing. C16329T and T6777C were also significantly associated among cases with serous histology, with ORs (95% CIs) of 6.13 (1.2-29.6) and 0.61 (0.43-0.87), respectively. Haplotype analysis for each of the three regions investigated revealed significant haplotype-disease associations; however, findings suggest that the respective associations were driven by the most significant SNP(s) listed above. This is the first large-scale epidemiologic study to provide evidence that SNPs in mitochondrial genes may be novel risk factors for ovarian cancer. Future investigation of additional mitochondrial variants (i.e. nuclear-encoded mitochondrial proteins) is necessary to more comprehensively investigate this association. Furthermore, replication of the most promising SNPs in a larger population is warranted to validate these findings. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2835.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.008 | 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".