Beyond the Socioeconomic Gradient: The Epigenetic Coefficient (EGC) as a Distribution-Sensitive Framework for Measuring Inequality in Epigenetic Ageing

Background/Objectives: Studies of socioeconomic differences in DNA methylation-based ageing mainly report regression coefficients, group contrasts, mediation estimates, or decompositions, which do not describe how complete epigenetic age acceleration (EAA) distributions differ across ordered socioeconomic strata. We developed the Epigenetic Coefficient (EGC) to address this gap. Methods: The study comprised two linked workstreams. First, we specified the EGC profile (EGC-M, a distributional magnitude based on weighted pairwise Wasserstein-1 distances; EGC-O, a conditional orientation; EGC-S, a rank-gradient companion; and L, the population mean burden) and verified the frozen version 1.0 point estimators through independent R (version 4.6.1) and Python (version 3.14.5) implementations, controlled datasets, and a small exploratory pilot. Second, a structured evidence map of 238 deduplicated publications was searched for equivalent methods. Results: R and Python agreed in 1235/1235 prespecified comparisons across 20 fixed datasets (maximum absolute difference 3.29 × 10−14). EGC-M detected distributional differences between strata with equal means. The pilot (N = 2500; five replications per condition) behaved coherently under null and gradient conditions but was not designed to estimate operating characteristics. In the evidence map, none of the 160 relevant publications described an equivalent coefficient, and eight near-direct precedents were audited in full text. Conclusions: The EGC is mathematically specified and reproducible across software. Its inferential calibration, biological validity, and incremental value over established inequality measures remain to be tested; it is therefore a candidate research framework.