APOE genotype and biological age impact inter-omic associations related to bioenergetics

Abstract

Apolipoprotein E (APOE) modifies human aging; specifically, the ε2 and ε4 alleles are among the strongest genetic predictors of longevity and Alzheimer's disease (AD) risk, respectively. However, detailed mechanisms for their influence on aging remain unclear. In the present study, we analyzed multi-omic association patterns across APOE genotypes, sex, and biological age (BA) axes in 2,229 community dwelling individuals. Our analysis, supported by validation in an independent cohort, identified diacylglycerols as the top APOE-associated plasma metabolites. However, despite the known opposing aging effects of the allele variants, both ε2- and ε4-carriers showed higher diacylglycerols compared to ε3-homozygotes. 'Omics association patterns of ε2-carriers and increased biological age were also counter-intuitively similar, displaying significantly increased associations between insulin resistance markers and energy-generating pathway metabolites. These results demonstrate the context-dependence of the influence of APOE, with ε2 potentially strengthening insulin resistance-like pathways in the decades prior to imparting its longevity benefits. Additionally, they provide an atlas of APOE-related 'omic associations and support the involvement of bioenergetic pathways in mediating the impact of APOE on aging.

Keywords: Alzheimer’s disease (AD); apolipoprotein E (APOE); biological age; insulin resistance; metabolism.

Figure 1

Study design to identify APOE genotype- and delta age-related alterations in the metabolome and inter-omic associations. Community dwelling individuals from the Arivale cohort were sorted based on delta age and APOE ε2 or ε4 carrier status. Metabolomic changes across APOE and delta age statuses were then analyzed. Finally, an inter-omic interaction analysis was performed to identify the effect modification of APOE or delta age status on inter-omic associations. These findings elucidate potential context-dependent relationships within APOE status and delta age group. Analyses were then repeated for validation with the TwinsUK cohort.

Figure 2

Lipids are the main APOE- and delta age-associated metabolites. (A–D) Volcano plots for the APOE E2 (A), APOE E4 (B), biologically younger (C), or biologically older (D) groups. For each metabolite, presented are the β-coefficient estimate and its log10 p-value from the GLM including metabolite abundance as the dependent variable, group statuses as the independent variables, and age, BMI, use of cholesterol medications, sex, and first two genetics principal components as the covariates (see Methods). Blue data points indicate a positive association between metabolite and test group with pre-adjusted p < 0.05, whereas orange points indicate a negative pre-adjusted association. Yellow highlighting indicates significance after multiple hypothesis testing (pFDR < 0.1, Benjamini–Hochberg method). n = 896 metabolites.

Figure 3

Biologically older males show similar multi-omic association signatures to APOE E2 males and biologically older females, particularly within central bioenergetic analytes. (A–C) Scatter plots of inter-omic analyte pairs with associations significantly modified by APOE E2 in males (A), and by biological oldness in males (B) and females (C). Line indicates simple linear regression, with shading indicating the 95% confidence interval. (D, E) Circos plots depicting the shared analyte associations (pFDR < 0.1, Benjamini-Hochberg method) between male APOE E2 and biologically older males (D), and between biologically older males and females (E). Associations specific to one group are connected with green and blue lines, whereas significant concordant associations shared in both groups are presented in red lines. Analyte nodes in associations significant to both groups are labeled.

Figure 4

TwinsUK validates lipids as top APOE associated metabolites. The β-coefficient estimates for the APOE E2 (A) and E4 (B) groups are plotted against their -log10 pre-adjusted p-value from the metabolite GLMs. Blue data points indicate a positive association between metabolite and test group with pre-adjusted p < 0.05, whereas orange points indicate a negative pre-adjusted association. Yellow highlighting indicates significance after multiple hypothesis testing (pFDR < 0.1, Benjamini-Hochberg method).