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Observational Study
.2015 Nov 15;212(10):1563-73.
doi: 10.1093/infdis/jiv277. Epub 2015 May 12.

HIV-1 Infection Accelerates Age According to the Epigenetic Clock

Affiliations
Observational Study

HIV-1 Infection Accelerates Age According to the Epigenetic Clock

Steve Horvath et al. J Infect Dis..

Abstract

Background: Infection with human immunodeficiency virus type 1 (HIV) is associated with clinical symptoms of accelerated aging, as evidenced by the increased incidence and diversity of age-related illnesses at relatively young ages and supporting findings of organ and cellular pathologic analyses. But it has been difficult to detect an accelerated aging effect at a molecular level.

Methods: Here, we used an epigenetic biomarker of aging based on host DNA methylation levels to study accelerated aging effects due to HIV infection. DNA from brain and blood tissue was assayed via the Illumina Infinium Methylation 450 K platform.

Results: Using 6 novel DNA methylation data sets, we show that HIV infection leads to an increase in epigenetic age both in brain tissue (7.4 years) and blood (5.2 years). While the observed accelerated aging effects in blood may reflect changes in blood cell composition (notably exhausted cytotoxic T cells), it is less clear what explains the observed accelerated aging effects in brain tissue.

Conclusions: Overall, our results demonstrate that the epigenetic clock is a useful biomarker for detecting accelerated aging effects due to HIV infection. This tool can be used to accurately determine the extent of age acceleration in individual tissues and cells.

Keywords: DNA methylation; HIV-1; aging; biomarker; epigenetics.

© The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

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Figures

Figure 1.
Figure 1.
Discovery brain data from human immunodeficiency virus (HIV)–infected subjects (cases) and HIV-uninfected subjects (controls).A–D, DNA methylation (DNAm) age versus chronological age in all brain samples (A) and occipital cortex (B), cerebellum (C), and frontal lobe (D) samples. Red squares and black triangles in the scatterplot denote samples from cases and controls, respectively. The orange line depicts a linear regression line through case samples. Similarly, the black solid line corresponds to a regression line of DNAm age on chronological age in control samples. For each subject (point), age acceleration is defined as the vertical distance to the black regression line (ie, DNAm age minus the expected value based on control samples).E, Mean age acceleration versus control status in all brain samples. Each bar plot depicts 1 standard error around the mean value and reports the Kruskal–Wallis (nonparametric) group comparison testP value. Analogous results can be obtained when restricting the analysis to occipital cortex (B andF) or cerebellar (C andG) samples but not for samples from the frontal lobe (D andG).E–H, The group comparisons in panelsE–H involved a total of 130, 72, 24, and 24, samples respectively. The number of samples in each group is reported by the rotated number under each bar.I–L, HIV load (log10 transformed) in cerebrospinal fluid (CSF) of cases versus age acceleration in all brain samples (I) and occipital cortex (J), cerebellum (K), and frontal lobe (L) samples. Abbreviation: cor, correlation.
Figure 2.
Figure 2.
Validation brain data from human immunodeficiency virus (HIV)–infected subjects (cases) and HIV-uninfected subjects (controls). Analogous to Figure 1, we used independent data sets (data 2 and 3) to relate HIV status to epigenetic age acceleration in the frontal lobe and cerebellum of cases and controls.A andB, DNA methylation (DNAm) age versus chronological age in cerebellum (A) and frontal lobe (B) samples. Points (subjects) are colored by HIV status: cases correspond to red squares. The orange and black lines depict regression lines case and control samples, respectively. The measure of age acceleration is the same as used in Figure 1.C andD, Age acceleration versus HIV status in cerebellum (C) and frontal lobe (D) specimens. Each bar plot reports the Kruskal–Wallis (nonparametric) group comparison testP value and 1 standard error around the mean. Abbreviation: cor, correlation.
Figure 3.
Figure 3.
Epigenetic age in blood tissue versus human immunodeficiency virus (HIV) status. The first column (A andC) and second column (B andD) report findings for blood data sets 4 and 5, respectively.A andB, DNA methylation (DNAm) age versus chronological age. Samples from HIV-infected patients (cases; points) are colored in red. The black solid line and the orange line correspond to regression lines through HIV-uninfected control samples and case samples, respectively. For each subject (point), age acceleration is defined as the vertical distance to the black regression line.C andD, Mean age acceleration versus HIV status. The rotated numbers on thex-axis report the group sizes. The bar graphs report 1 standard error and a Kruskal–Wallis testP value. Abbreviation: cor, correlation.
Figure 4.
Figure 4.
Age acceleration versus blood cell counts in human immunodeficiency virus (HIV)–infected subjects (cases). Here we used DNA methylation (DNAm) data from peripheral blood mononuclear cells from cases (data set 6).A, DNAm age versus age. The red line indicates the regression line. The black line corresponds toy =x. Epigenetic age acceleration (defined as the residual) versus the percentage of natural killer (NK) cells (B), CD14+ monocytes (C), granulocytes (D), CD4+ T cells (E), CD8+ T cells (F), naive CD8+ T cells (G), and exhausted (CD28−CD45RA−) CD8+ T cells (H).
Figure 5.
Figure 5.
Age acceleration versus blood cell counts in HIV-uninfected control subjects (controls). The first 2 rows (A–H) and the last 2 rows (I–P) present results for controls from blood data sets 5 and 7, respectively.A andI, DNA methylation (DNAm) age versus chronological age. Age acceleration was defined as the residual resulting from the regression line (red line). Age acceleration versus natural killer (NK) cells (B andJ), CD14+ monocytes (C andK), granulocytes (D andL), CD4+ T cells (E andM), CD8+ T cells (F andN), naive CD8+ T cells (G andO), and exhausted (CD28−CD45RA−) CD8+ T cells (H andP). The blood cell abundance measures were estimated on the basis of DNAm data (“Methods” section).
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