Joint Analysis of Nuclear and Mitochondrial Variants in Age-Related Macular Degeneration Identifies Novel Loci <i>TRPM1</i> and <i>ABHD2/RLBP1</i>
Bibliographic record
Abstract
Purpose: Presently, 52 independent nuclear single nucleotide polymorphisms (nSNPs) have been associated with age-related macular degeneration (AMD) but their effects do not explain all its variance. Genetic interactions between the nuclear and mitochondrial (mt) genome may unearth additional genetic loci previously unassociated with AMD risk. Methods: Joint effects of nSNPs and selected mtSNPs were analyzed by two degree of freedom (2df) joint tests of association in the International AMD Genomics Consortium (IAMDGC) dataset (17,832 controls and 16,144 advanced AMD cases of European ancestry). Subjects were genotyped on the Illumina HumanCoreExome array. After imputation using MINIMAC and the 1000 Genomes Project Phase I reference panel, pairwise linkage disequilibrium pruning, and quality control, 3.9 million nSNPs were analyzed for interaction with mtSNPs chosen based on association in this dataset or publications: A4917G, T5004C, G12771A, and C16069T. Results: Novel locus TRPM1 was identified with genome-wide significant joint effects (P < 5.0 × 10-8) of two intronic TRPM1 nSNPs and AMD-associated nonsynonymous MT-ND2 mtSNP A4917G. Stratified analysis by mt allele identified an association only in 4917A (major allele) carriers (P = 4.4 × 10-9, odds ratio [OR] = 0.90, 95% confidence interval [CI] = 0.87-0.93). Intronic and intergenic ABHD2/RLBP1 nSNPs demonstrated genome-wide significant joint effects (2df joint test P values from 1.8 × 10-8 to 4.9 × 10-8) and nominally statistically significant interaction effects with MT-ND5 synonymous mtSNP G12771A. Although a positive association was detected in both strata, the association was stronger in 12771A subjects (P = 0.0020, OR = 2.17, 95% CI = 1.34-3.60). Conclusions: These results show that joint tests of main effects and gene-gene interaction reveal associations at some novel loci that were missed when considering main effects alone.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".