The KORA‐AGE Eye Study: Genetic Susceptibility
Bibliographic record
Abstract
Abstract Purpose To estimate the genetic susceptibility of major age‐related eye diseases in a population‐based study in the region of Augsburg, Southern Germany (KORA). Methods 822 persons aged 68‐96 years from the KORA‐AGE study were asked in a follow up 2012 in a standardized interview for the presence of major eye disorders like cataracts, glaucoma and age‐related macula degeneration (AMD). In validated cases we investigated genetic susceptibility for major eye diseases by association with 31 functional candidate genes; association was calculated using logistic regression adjusted for age and gender. Results 465 persons reported any eye disorder (57%); 71% of them could be validated and specified. There were 68 cases of AMD and 72 cases of glaucoma; 90 % of glaucoma and 93% of AMD are overlapping with cataracts resulting in 182 pure cataracts and 117 cataracts with glaucoma and/or AMD. In a recessive model, only ARMS2 (age‐related maculopathy susceptibility gene 2) showed significant (p=0.0000175) association with AMD (OR 9.0; 95%‐CI 3.8 – 21.4). This gene is present only in humans and chimpanzees, but not in rodents. Additionally, CRYBA1 (encoding βA1‐crystallin) showed an increased risk for glaucoma (OR 5.8; 95%‐CI 1.7 – 20.5), however it is statistically not significant (p=0.144). These effects might be due to a relatively small sample size. Conclusion Age‐related eye diseases frequently do not occur in their “pure” form; cataracts overlap frequently with glaucoma and/or AMD. The association of AMD with ARMS2 strongly supports previous findings of ARMS2 as a major risk gene for AMD. This study was supported by the BMBF (FKZ 01ET1003A)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".