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Updated: Aug 16, 2026
A Phenotyping Regimen for Genetically Modified Mice Used to Study Genes Implicated in Human Diseases of Aging
Published on: July 14, 2016
Integrative genomic and proteomic analyses identify candidate genetic loci and genetically supported proteins in
Ning Chen1, Yukang Liu1, Zejun Chen1
1The Second School of Clinical Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Background:
Age-related macular degeneration (AMD) is a leading cause of visual impairment; however, robust drug targets for primary prevention remain elusive. This study aimed to identify candidate genetic loci and putative genetically supported proteins for AMD through integrative genomics and proteomics.
Methods:
A genome-wide association study (GWAS) meta-analysis (28,543 cases and 1,072,092 controls) was performed to identify risk loci, followed by proteome-wide Mendelian randomization (MR), colocalization, and multi-omics summary-data-based MR with heterogeneity in dependent instruments (SMR-HEIDI) analyses to infer genetically supported proteins. Functional characterization included gene enrichment, single-cell RNA sequencing, mediation across 731 immunophenotypes, and a mouse knockout assessment. Druggability was evaluated using the Drug-Gene Interaction Database.
Results:
The GWAS meta-analysis identified 10 candidate genetic loci for AMD (including three previously reported and seven newly identified loci). Proteome-wide MR and colocalization analyses uncovered 23 genetically supported plasma proteins (11 risk and 12 protective factors). Multi-omics SMR-HEIDI analysis prioritized LAMC2 and PLTP as first-tier risk genes, which was consistently supported across protein, expression, and methylation levels. Single-cell RNA sequencing revealed cell-type-specific enrichment of key genes in monocytes and stromal/progenitor-like cells within AMD retinas, and subsequent mediation analysis identified specific immune traits, most notably regulatory T-cell subsets, as potential partial mediators of AMD risk. Druggability assessment identified 15 target genes, and bioinformatic enrichment nominated cyclophosphamide. Given the toxicity profile of cyclophosphamide, this computational finding serves strictly as a pathway indicator, reinforcing the broader therapeutic relevance of modulating the identified immune-related targets.
Conclusion:
Our integrative analyses identified candidate genetic loci and genetically supported proteins for AMD, providing a foundation for translating genomic findings toward primary prevention. The exploratory nature of this study highlights the need to experimentally validate the proposed targets and underlying mechanisms.
