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Genetic Associations of Primary Angle-Closure Disease

2024· review· en· W4393278341 on OpenAlexaboutno aff
Yu Liang, Yu Yao Wang, Shi Song Rong, Zhen Ji Chen, Shu Ying Chen, Jenson A. Tham, Poemen P. Chan, Jason C. Yam, Janey L. Wiggs, Chi Pui Pang, Clement C. Tham, Li Jia Chen

Bibliographic record

VenueJAMA Ophthalmology · 2024
Typereview
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineClosure (psychology)DiseaseGeneticsInternal medicineBiology

Abstract

fetched live from OpenAlex

Importance: Effects of genetic variants on primary angle-closure disease remained uncertain. Objective: To systematically review the associations of common single-nucleotide variants (SNVs) and rare coding variants with primary angle-closure disease, its subtypes (including primary angle-closure glaucoma, primary angle-closure suspect, and primary angle-closure) and progression. Data Sources: Eligible studies from PubMed, Embase, and Web of Science were retrieved up to April 3, 2023. SNV information was extracted from eligible reports and 2 genome-wide association studies summary statistics, UK BioBank and FinnGen. Study Selection: Studies providing analyzable genotype or allele data in a case-control design for primary angle-closure disease association and longitudinal case-only design for primary angle-closure disease progression. Data Extraction and Synthesis: PRISMA guidelines were used for literature screening and the Newcastle Ottawa Scale for data quality assessment. Pooled effect size with 95% CIs of SNV associations were calculated using fixed- or random-effect models according to I2 statistics. Main Outcomes and Measures: SNVs reported in 2 or more studies were meta-analyzed to generate pooled odds ratios and P values. Common and rare coding variants from single reports were summarized. Results: Sixty-nine citations were eligible for meta-analysis on overall primary angle-closure disease, involving 206 SNVs in 64 genes or loci. Seventeen SNVs in 15 genes or loci showed associations with primary angle-closure disease, and 15 SNVs in 13 genes or loci showed associations with primary angle-closure glaucoma. Two SNVs, ABCA1 rs2422493 and ZNRF3 rs3178915, were associated only with primary angle-closure disease. Two SNVs, PCMTD1-ST18 rs1015213 and COL11A1 rs3753841, were associated with primary angle-closure suspect, and 1 SNV, MMP9 rs3918249, was associated with primary angle-closure. This systematic review and meta-analysis newly confirmed 7 genes or loci associated with primary angle-closure glaucoma: ATOH7, CALCRL, FBN1, IL6, LOXL1, MMP19, and VAV3. Common and rare coding variants in 16 genes or loci that have been associated with primary angle-closure disease were cataloged. Stratification analysis revealed different primary angle-closure disease-associated genes in different ethnic populations. Only 1 study regarding the genetic association of primary angle-closure glaucoma progression was identified. Conclusions and Relevance: This study revealed the genetic complexity of primary angle-closure disease, involving common SNVs and rare coding variants in more than 30 genes or loci, with ethnic and phenotypic diversities. Further replication, genotype-phenotype correlation, and pathway analyses are warranted.

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)0.011
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0030.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.350
Teacher spread0.294 · 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 designNot applicable
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

Citations9
Published2024
Admission routes1
Has abstractyes

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