rs117044564 (C1QBPP1/LINC01683): AMD and VLDL

Key takeaways

• A UK Biobank study of 72,376 people found 84 blood metabolites linked to AMD (age-related macular degeneration), the leading cause of irreversible vision loss in older adults.
• Very small VLDL (very low-density lipoprotein) subclasses appear to causally contribute to AMD development, not just correlate with it.
• Age remains the strongest single predictor of AMD risk; metabolites add only a small incremental contribution.
• Causal evidence comes from Mendelian randomization, an inferential method, not a clinical trial.
• The individual contribution of rs117044564 is not reported separately in the available study text.

What the research says A three-tiered analysis of 325 blood metabolites in 72,376 UK Biobank participants (1,353 AMD cases, 71,023 controls) identified 84 metabolic markers significantly associated with AMD after false discovery rate adjustment (FDR-adjusted p < 0.05). Nineteen of those metabolites showed evidence of a likely causal role in AMD via two-sample Mendelian randomization (an inferential technique that uses genetic variants as proxies for metabolite levels to estimate causality), with six very small VLDL subclasses and phospholipid to total lipid ratios in medium VLDL being prominent among them. Metabolite GWAS (genome-wide association study) was conducted in 98,316 European participants from the same cohort.

Reported associations

• Age-related macular degeneration (AMD): This locus was examined within a genome-wide metabolite analysis identifying 84 AMD-associated metabolic markers across 72,376 UK Biobank participants.
• Very small VLDL levels: Depleted circulating very small VLDL was one of 19 metabolites identified as likely causally contributing to AMD, with all six very small VLDL subclasses implicated.
• Phospholipid to total lipid ratio in medium VLDL: Altered phospholipid ratios in medium VLDL were also among the 19 likely causal metabolites identified.
• AMD risk prediction: Age was identified as the primary predictive factor in a machine learning risk model, with metabolites providing a much smaller additional contribution beyond age and sex.

Evidence quality The underlying study is a large UK Biobank observational cohort analysis (1,353 AMD cases among 72,376 total participants; metabolite GWAS in 98,316 European participants). Causal inference relies on two-sample Mendelian randomization, which requires that genetic instruments serve as valid proxies for metabolite levels and are not confounded by unrelated biological pathways, conditions that may not always hold. No p-values or effect sizes specific to rs117044564 individually are reported in the available text, and replication in independent cohorts is not described. Findings for this locus should be considered preliminary.

Lifestyle considerations No lifestyle considerations on file for this variant.