Array-Based Epigenetic Aging Indices May Be Racially Biased

Abstract

Epigenetic aging (EA) indices are frequently used as predictors of mortality and other important health outcomes. However, each of the commonly used array-based indices has significant heritable components which could tag ethnicity and potentially confound comparisons across racial and ethnic groups. To determine if this was possible, we examined the relationship of DNA methylation in cord blood from 203 newborns (112 African American (AA) and 91 White) at the 513 probes from the Levine PhenoAge Epigenetic Aging index to ethnicity. Then, we examined all sites significantly associated with race in the newborn sample to determine if they were also associated with an index of ethnic genetic heritage in a cohort of 505 AA adults. After Bonferroni correction, methylation at 50 CpG sites was significantly associated with ethnicity in the newborn cohort. The five most significant sites predicted ancestry with a receiver operator characteristic area under the curve of 0.97. Examination of the top 50 sites in the AA adult cohort showed that methylation status at 11 of those sites was also associated with percentage European ancestry. We conclude that the Levine PhenoAge Index is influenced by cryptic ethnic-specific genetic influences. This influence may extend to similarly constructed EA indices and bias cross-race comparisons.

DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function

“…Nevertheless, future kidney research would benefit from the development and use of methods relying on filtration markers independent from muscle mass and/or moving beyond race as a variable [ 78 ]. The lack of trans-ethnic replication of all associations may be explained by multiple factors, most notably the smaller sample sizes from non-European studies, or ethnic biases in DNAm-based predictors (as those reported for PhenoAge in [ 80 ]). Future studies using larger, homogeneous sample sizes from diverse ethnic groups are needed to address the generalizability of our findings, and to interrogate the contributions of environmental and social determinants of health disparities in epigenetic aging.…”

Adopting a “Compound” Exposome Approach in Environmental Aging Biomarker Research: A Call to Action for Advancing Racial Health Equity

“…Although the authors should be recognized for their efforts, making such concessions about the use of simplified race correlations and singular measures of SES (e.g., poverty solely based on income), in our opinion, is insufficient when one considers the implications that these studies can have on policy and clinical practice. An additional impetus for requiring more from simplified race correlations comes from more recent studies of epigenetic aging that demonstrate race-based DNA methylation array biases ( Philibert et al. 2020 ), and studies that report associations of increased epigenetic aging with exposure to violence ( Jovanovic et al.…”

A simple, rapid, interpretable, actionable and implementable digital PCR based mortality index

“…The FACHS PC cohort is the adult component in a longitudinal study begun in 1997 of the effects of psychosocial factors on health-related outcomes of 889 African American parent-child dyads [36]. The current biological and clinical data, whose collection and preparation have been described elsewhere, are taken from Wave 5 of the FACHS PC study (2008--2010) [16]. All procedures in the FACHS study were approved by the University of Iowa IRB (IRB 200802719).…”

“…The preparation of data from 2256 FHS Offspring Cohort subjects used in this study have been described elsewhere [16,28]. After downloading, the genome-wide methylation data (Infinium Methylation450 BeadChip (Illumina, San Diego, CA)) from 2,567 individuals of the Offspring Cohort who participated in the Framingham Offspring 8 th exam (2005 to 2008) were extracted and then were subjected to DASEN normalization using the MethyLumi, WateRmelon, and IlluminaHumanMethylation450k.db R packages [38].…”

“…Two of the leading algorithms, the Levine PhenoAge Index (h 2 = 0.51) and the recently introduced GrimAge index (h 2 = 0.37) have significant heritability [9,15]. In previous work, we have shown that some of the 513 sites used in the Levine PhenoAge Index can be used to predict ancestry and that this may result in bias that interferes with risk prediction in African American subjects [16]. Whether this is true for other indices is not known and we note that the 1030 probes used in the GrimAge index has not been publicly disclosed [15].…”