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Record W4403626248 · doi:10.1038/s41467-024-53212-6

Uncovering genetic loci and biological pathways associated with age-related cataracts through GWAS meta-analysis

2024· review· en· W4403626248 on OpenAlexfundno aff
Santiago Díaz‐Torres, Samantha Sze‐Yee Lee, Luis M. García‐Marín, Adrián I. Campos, Gareth Lingham, Jue‐Sheng Ong, David A. Mackey, Kathryn P. Burdon, Michael Hunter, Xianjun Dong, Stuart MacGregor, Puya Gharahkhani, Miguel E. Rentería

Bibliographic record

VenueNature Communications · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsnot available
FundersMurdoch UniversityUniversity of Notre Dame AustraliaAlcon Research InstituteGovernment of Western AustraliaEdith Cowan UniversityCurtin University of TechnologyNational Health and Medical Research CouncilWomen and Infants Research FoundationRaine Medical Research FoundationAustralian GovernmentCanadian Institutes of Health ResearchUniversity of QueenslandOphthalmic Research Institute of AustraliaRebecca L. Cooper Medical Research FoundationMedical Research CouncilUniversity of Notre Dame
KeywordsGenome-wide association studyMeta-analysisCataractsComputational biologyGeneticsBiologyBioinformaticsMedicineSingle-nucleotide polymorphismGenotypeGene

Abstract

fetched live from OpenAlex

Age-related cataracts is a highly prevalent eye disorder that results in the clouding of the crystalline lens and is one of the leading causes of visual impairment and blindness. The disease is influenced by multiple factors including genetics, prolonged exposure to ultraviolet radiation, and a history of diabetes. However, the extent to which each of these factors contributes to the development of cataracts remains unclear. Our study identified 101 independent genome-wide significant loci, 57 of which are novel. We identified multiple genes and biological pathways associated with the cataracts, including four drug-gene interactions. Our results suggest a causal association between type 1 diabetes and cataracts. Also, we highlighted a surrogate measure of UV light exposure as a marker of cataract risk in adults. Here, the authors expand knowledge of the genetic architecture of age-related cataracts, exploring associated pathways and drug-gene interactions, and clarify the roles of type 1 diabetes and UV exposure in cataract etiology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.119
GPT teacher head0.357
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

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