Obesity accelerates epigenetic aging of human liver

Abstract

Because of the dearth of biomarkers of aging, it has been difficult to test the hypothesis that obesity increases tissue age. Here we use a novel epigenetic biomarker of aging (referred to as an "epigenetic clock") to study the relationship between high body mass index (BMI) and the DNA methylation ages of human blood, liver, muscle, and adipose tissue. A significant correlation between BMI and epigenetic age acceleration could only be observed for liver (r = 0.42, P = 6.8 × 10(-4) in dataset 1 and r = 0.42, P = 1.2 × 10(-4) in dataset 2). On average, epigenetic age increased by 3.3 y for each 10 BMI units. The detected age acceleration in liver is not associated with the Nonalcoholic Fatty Liver Disease Activity Score or any of its component traits after adjustment for BMI. The 279 genes that are underexpressed in older liver samples are highly enriched (1.2 × 10(-9)) with nuclear mitochondrial genes that play a role in oxidative phosphorylation and electron transport. The epigenetic age acceleration, which is not reversible in the short term after rapid weight loss induced by bariatric surgery, may play a role in liver-related comorbidities of obesity, such as insulin resistance and liver cancer.

Keywords: DNA methylation; aging; biological age; epigenetics; obesity.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Discovery analysis. Analysis of the correlation of DNAm age to chronological age across the publicly available datasets: (A–D) This row shows the correlation of chronological age to the DNAm age in liver, adipose tissue, muscle, and blood. The red dashed line in these panels indicates the regression line. In all panels (A–H), each point corresponds to a human subject. Red circles indicate women and blue squares are used to denote male individuals. The age acceleration effect for each subject (point) corresponds to the vertical distance to the red regression line. (E–H) This row plots the relation of BMI and age acceleration in those tissues. The black horizontal line (y = 0) corresponds to an age acceleration of zero. It is evident that only liver tissue shows a significant correlation (r = 0.42, P = 6.8 × 10−4) to BMI.

Fig. 2.

Replication analysis. Independent liver (A, B, E, F), adipose tissue (C and G), and muscle (D and H) datasets were analyzed for a correlation of chronological age and DNAm age and age acceleration to BMI. The data confirm the correlation of DNAm age acceleration and BMI in liver tissue (E and F), even if the analysis is restricted to individuals without histological evidence of NAFLD (i.e., controls and healthy obese subjects) (F) and the lack of this correlation in adipose and muscle tissue (G and H).

Fig. 3.

Post hoc analyses of subgroups and histological characteristics of NASH. An adjusted measure of DNAm age is related to various measures of liver pathology. The adjusted measure of DNAm age acceleration was defined as residual from a regression model that regressed DNAm age on chronological age+BMI+sex. Note that this adjusted measure of age acceleration does not relate to (A) NAS, (B) fat percentage (steatosis), (C) inflammation, and (D) fibrosis. Each scatterplot reports the Pearson correlation coefficient and P value. Analogous results can also be found in the individual liver datasets (Figs. S3 and S4).

Fig. 4.

Effect of weight loss and exercise intervention on DNAm age. For 21 subjects, liver methylation data were available before and after bariatric surgery. As expected, BMI drops significantly within 6–9 mo following bariatric surgery (A). However, the DNAm age of the liver tissue is unaffected (B). (C) DNAm age of adipose tissue is unaffected by a 6-mo exercise intervention (20).