Integrating genetics and metabolomics from multi-ethnic and multi-fluid data reveals putative mechanisms for age-related macular degeneration

Abstract

Age-related macular degeneration (AMD) is a leading cause of blindness in older adults. Investigating shared genetic components between metabolites and AMD can enhance our understanding of its pathogenesis. We conduct metabolite genome-wide association studies (mGWASs) using multi-ethnic genetic and metabolomic data from up to 28,000 participants. With bidirectional Mendelian randomization analysis involving 16,144 advanced AMD cases and 17,832 controls, we identify 108 putatively causal relationships between plasma metabolites and advanced AMD. These metabolites are enriched in glycerophospholipid metabolism, lysophospholipid, triradylcglycerol, and long chain polyunsaturated fatty acid pathways. Bayesian genetic colocalization analysis and a customized metabolome-wide association approach prioritize putative causal AMD-associated metabolites. We find limited evidence linking urine metabolites to AMD risk. Our study emphasizes the contribution of plasma metabolites, particularly lipid-related pathways and genes, to AMD risk and uncovers numerous putative causal associations between metabolites and AMD risk.

Keywords: AMD; CLSA; Canadian Longitudinal Study of Aging; GWASs; HCHS/SOL; HPFS; Health Professionals Follow Up Study; Hispanic Community Health Study/Study of Latinos; MR; Mendelian randomization; NHS; Nurses’ Health Study; UK Biobank; age-related macular degeneration; genome-wide association studies; genomics; metabolomics.

Graphical abstract

Figure 1

Overview of the study design

Figure 2

Circular Manhattan plot illustrating metabolite-based genome-wide association studies The circular Manhattan plot displays the p values from metabolite-based genome-wide association studies (mGWASs). Each circle represents an mGWAS in a specific study. From innermost to outermost circle: NHS/NHSII/HPFS, Canadian Longitudinal Study on Aging (CLSA), Metabolic Syndrome in Men (METSIM) study, HCHS/SOL, plasma meta-analysis, and urine meta-analysis. The circular Manhattan plot is customized to display all genome-wide significant SNPs (p < 5 × 10⁻⁸) for available metabolites in each study, with p values truncated at 1 × 10⁻⁵⁰.

Figure 3

Multi-ancestry and multi-fluid validation of mQTLs across different studies These plots show the effect sizes for metabolomic quantitative trait loci (mQTLs) from various datasets, labeled on the x and y axes. mQTLs were selected from the studies labeled on the x axis. Effect sizes are represented as green dots, while the 1.96 standard errors are depicted as gray bars (vertical and horizontal error bars). The red lines indicate the best-fit lines, and the 95% confidence intervals are shown in gray. The plasma meta-analysis included plasma metabolites from NHS/NHSII/HPFS, CLSA, METSIM, HCHS/SOL, and AMD Biomarker Study (Boston and Portugal plasma data). The urine meta-analysis included urine metabolites from Schlosser et al. (urine) and AMD Biomarker Study (Boston and Portugal urine data). p = 0 signifies a very small p value in R (smaller than the smallest representable positive double-precision floating point value at 2.225074 × 10⁻³⁰⁰).

Figure 4

Replication of MR estimates for the associations between metabolites and AMD from NHS, NHSII, HPFS, CLSA, METSIM, and HCHS/SOL (A) The replication of 19 overlapping metabolites between NHS/NHSII/HPFS, CLSA, METSIM, and HCHS/SOL. The x axis represents the effect size (beta) of metabolites on advanced AMD risk, while the vertical dashed line corresponds to beta = 0. Four MR methods are depicted with different colors and line types (inverse-variance weighted method, weighted median, weighted mode, and MR-Egger). For metabolites with a single SNP as a genetic instrument, the Wald ratio method is used (grouped into the inverse-variance weighted method). (B) Comparison of the MR Z scores (MR effect sizes divided by standard errors) from plasma meta-analysis (x axis) and each individual study (y axis). The "MR discovery" indicates whether a metabolite is associated with advanced AMD risk in the plasma meta-analysis. Significant MR p values in each study (MR replication) are denoted by red dots (FDR p < 0.05).

Figure 5

Prioritized metabolite pathways from Mendelian randomization analysis The x axis displays the names of subpathways (biochemical groups, with “chemical” representing xenobiotics), while the y axis indicates the number of metabolites (with at least two metabolites) associated with advanced AMD risk.

Figure 6

Colocalization analysis identifies 114 shared causal variants between metabolite and AMD pairs The x axis displays the nearest gene name for each shared variant between metabolites and AMD. The y axis represents the number of genes identified in the colocalization analysis. “AMD index SNP” refers to the colocalization analysis for AMD SNPs within a 2 Mb genomic window, and “metabolite index SNP” pertains to the colocalization analysis for metabolite SNPs within a 2 Mb genomic window.

Figure 7

Comparison of results from metabolome-wide association study and Mendelian randomization analysis The four panels depict the Z scores (association Z statistics) from the MWAS and four MR methods (MR effect sizes divided by standard errors from weighted median, weighted mode, inverse-variance weighted method, and MR-Egger). The x axis shows the Z scores for 155 metabolites that were associated with AMD risk in the MWAS analysis after adjusting for multiple testing. The y axis presents the Z scores from MR analysis. An MR evidence of 1 (displayed in red) indicates that a metabolite is associated with AMD risk from MR analysis after adjusting for multiple testing.