A literature search was conducted in PubMed and Web of Science via (age-related Macular Degeneration NOT review[ptyp] AND English [LA]) AND (indel[tiab] OR substitution[tiab] OR deletion[tiab] OR insertion[tiab] OR polymorphism*[tiab] OR SNP [tiab] OR SNPs[tiab] OR variation*[tiab] OR variant*[tiab] OR mutation[tiab] OR transition[tiab] OR translation[tiab])) by one author (DY.W). All the literature was searched up to 2024--06 and was manually read to screen relevant studies. Two other authors (DY. W and YY. W) independently screened the remaining full-text references and reviewed the reference lists of other eligible studies. Disagreements between the authors were discussed with the third author (M. Z.) for a final decision. All the literature data will be manually collected, labeled, annotated, and expanded. All the data recorded in AMDGKB were collected via manual text mining and selected according to the Age-Related Eye Disease Study (ARED) criteria.

The inclusion criteria for this study includes:

• AMD and polypoid chorioretinal vasculopathy (PCV) diagnosed by the gold standard mentioned based on reference standards;
• Population with an average age of over 50 years old;
• Studies offered information on human genetic and SNP detection;
• No extra retinal vitreous disorders, including high myopia, diabetic retinopathy or early onset retinal degenerative, etc.

The following conditions are excluded:

• Disorders of the retina and vitreous other than AMD or PCV;
• Information related to a single gene in a multivariate model with additional factors;
• Letters and reports with insufficient information;
• META analysis using previous available data;
• Articles that cannot be obtained;
• Animal experiments.

This database applied the Age-Related Eye Disease Study (AREDs) as diagnostic criteria to minimize bias. Early AMD was characterized by the presence of at least medium-sized drusen (diameter≥63μm ). Advanced AMD was defined as the presence of neovascular AMD (or wet AMD) or geographic atrophy in at least one eye. This analysis comprised trials that recruited PCV and nAMD patients separately.

To control data quality, literature with unclear and confusing conclusions was deemed insufficient for inclusion in the database. After screening the literature, following information in the literature was collected and organized:

1. Information collection

• Research information, including country/region, research type, and research method;
• Cohort information, including race, gender and average age;
• Disease information, including disease subtypes, comorbidities (hypertension, diabetes, hyperlipidemia, BMI, family history, blood lipid concentration, etc.), best corrected visual acuity,and retinal thickness;
• Treatment information, including treatment plan, treatment drugs, combined treatment, and treatment cycle;
• Gene/SNP information, including samples, sequencing methods, statistical models, Minor Allele Frequency(MAF), and statistical results(P value, odd ratio).

2. Data annotation and expansion

Extract information from public databases for artificial data annotation and expansion of genes and SNPs, including NCBI, HPA, HGNC, Uniprot, OMIM, PDB, Gene Ontology, g:Profiler, KEGG. To provide insight into the biology of the collected genes, we retrieved comprehensive biological functional annotations from public resources，which links are included in the database.

2.1 Genetic data annotation and expansion

• Basic information: location, name, HGVS, Alleles;
• Gene type: Protein-coding; RNA, long noncoding; pseudogene; Phosphodiesterases;
• Classification of gene location: nuclear DNA, mitochondrial DNA, and chromosome location;
• Gene structure: including PDB and meme-motif;
• Gene expression;
• Related pathways from Gene Ontology and KEGG;
• Related diseases.

2.2 SNP data Labeling and expansion

• Basic information including gene, mutation type, mutation site, base change, and HGVS;
• Residual Changes;
• Pathway information;
• Associated diseases.

The AMDGKB database is available online at http://amdgd.bioinf.org.cn. Flask 1.1.2 is used as the background management system of the website. Meanwhile, we have employed MySQL 5.7 to manage the website’s database, and Ngnix to deploy the website. The website’s front-end employs the Boostrap v4.0 framework, calling jquery.dataTables.js and echart.js to draw the tables and figures