Appraising the Associations Between Systemic Iron Status and Epigenetic Clocks: A Genetic Correlation and Bidirectional Mendelian Randomization Study

May 5, 2023The American journal of clinical nutrition

Links Between Body Iron Levels and Biological Aging Clocks Using Genetic Analysis

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Abstract

Increased levels of ferritin and transferrin saturation are associated with elevated measures of epigenetic age acceleration.

Genetic correlations were observed between serum iron and PhenoAge (Rg = 0.1971, P = 0.048) and between transferrin saturation and PhenoAge (Rg = 0.196, P = 0.0469).
Increases in ferritin and transferrin saturation were linked to significant increases in all four measures of epigenetic age acceleration (all P < 0.0125, β > 0).
A standard deviation increase in serum iron was significantly associated with increased intrinsic epigenetic age acceleration (IEAA) and HannumAge acceleration (β: 0.36 and 0.32, respectively).
Transferrin showed suggestive evidence of a causal effect on epigenetic age acceleration (0.0125 < P < 0.05).
Reverse analyses indicated no significant causal effect of epigenetic clocks on systemic iron status.

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BACKGROUND: Genetic correlations (Rg) and bidirectional causal effects between systemic iron status and epigenetic clocks have not been fully investigated, although observational studies have suggested systemic iron status is associated with human aging.

OBJECTIVES: We explored the genetic correlations and bidirectional causal effects between systemic iron status and epigenetic clocks.

METHODS: Leveraging large-scale genome-wide association study summary-level statistics for 4 systemic iron status biomarkers (ferritin, serum iron, transferrin, and transferrin saturation) (N = 48,972) and 4 measures for epigenetic age (GrimAge, PhenoAge, intrinsic epigenetic age acceleration (IEAA), and HannumAge) (N = 34,710), genetic correlations, and bidirectional causal effects were estimated between them mainly by applying linkage disequilibrium score (LDSC) regression, Mendelian randomization (MR), and MR based on Bayesian model averaging. The main analyses were conducted employing multiplicative random-effects inverse-variance weighted MR. MR-Egger, weighted median, weighted mode, and MR-PRESSO were performed as sensitivity analyses to support the robustness of causal effects.

RESULTS: The LDSC results illustrated Rg between serum iron and PhenoAge (Rg = 0.1971, P = 0.048) and between transferrin saturation and PhenoAge (Rg = 0.196, P = 0.0469). We found that increased ferritin and transferrin saturation significantly increased all 4 measures of epigenetic age acceleration (all P < 0.0125, β > 0). Each standard deviation genetically increases in serum iron only significantly associated with increased IEAA (β: 0.36; 95% CI: 0.16, 0.57; P = 6.01 × 10) and increased HannumAge acceleration (β: 0.32; 95% CI: 0.11, 0.52; P = 2.69 × 10). Evidence showed a suggestively significant causal effect of transferrin on epigenetic age acceleration (all 0.0125 <P < 0.05). Additionally, reverse MR study indicated no significant causal effect of epigenetic clocks on systemic iron status. -4 -3

CONCLUSIONS: All 4 iron status biomarkers had a significant or suggestively significant causal effect on epigenetic clocks, whereas reverse MR studies did not.

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Appraising the Associations Between Systemic Iron Status and Epigenetic Clocks: A Genetic Correlation and Bidirectional Mendelian Randomization Study

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