A genetic variant in NRP1 is associated with worse response to ranibizumab treatment in neovascular age-related macular degeneration
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to investigate the role of single-nucleotide polymorphisms (SNPs) located in the neuropilin-1 (NRP1) gene in treatment response to antivascular endothelial growth factor (VEGF) therapy for neovascular age-related macular degeneration (nvAMD). METHODS: Four SNPs in the NRP1 gene (rs2229935, rs2247383, rs2070296, and rs2804495) were genotyped in a study cohort of 377 nvAMD patients who received the loading dose of three monthly ranibizumab injections. Treatment response was assessed as the change in visual acuity after three monthly loading injections compared with baseline. RESULTS: SNP rs2070296 was associated with change in visual acuity after 3 months of treatment. Patients carrying the GA or AA genotypes performed significantly worse than individuals carrying the GG genotype (P=0.01). A cumulative effect of rs2070296 in the NRP1 gene and rs4576072 located in the VEGF receptor 2 (VEGFR2 or KDR) gene, previously associated with treatment response, was observed. Patients carrying two risk alleles performed significantly worse than patients carrying zero or one risk allele (P=0.03), and patients with more than two risk alleles responded even worse to the therapy (P=3×10). The combined effect of these two SNPs on the response was also seen after 6 and 12 months of treatment. CONCLUSION: This study suggests that genetic variation in NRP1, a key molecule in VEGFA-driven neovascularization, influences treatment response to ranibizumab in nvAMD patients. The results of this study may be used to generate prediction models for treatment response, which in the future may help tailor medical care to individual needs.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".