Integrative Genetic Variation, DNA Methylation, and Gene Expression Analysis of Escitalopram and Aripiprazole Treatment Outcomes in Depression: A CAN-BIND-1 Study.

INTRODUCTION: Little is known about the interplay between genetics and epigenetics on antidepressant treatment (1) response and remission, (2) side effects, and (3) serum levels. This study explored the relationship among single nucleotide polymorphisms (SNPs), DNA methylation (DNAm), and mRNA levels of four pharmacokinetic genes, CYP2C19, CYP2D6, CYP3A4, and ABCB1, and its effect on these outcomes. METHODS: The Canadian Biomarker Integration Network for Depression-1 dataset consisted of 177 individuals with major depressive disorder treated for 8 weeks with escitalopram (ESC) followed by 8 weeks with ESC monotherapy or augmentation with aripiprazole. DNAm quantitative trait loci (mQTL), identified by SNP-CpG associations between 20 SNPs and 60 CpG sites in whole blood, were tested for associations with our outcomes, followed by causal inference tests (CITs) to identify methylation-mediated genetic effects. RESULTS: Eleven cis-SNP-CpG pairs (q<0.05) constituting four unique SNPs were identified. Although no significant associations were observed between mQTLs and response/remission, CYP2C19 rs4244285 was associated with treatment-related weight gain (q=0.027) and serum concentrations of ESCadj (q<0.001). Between weeks 2-4, 6.7% and 14.9% of those with *1/*1 (normal metabolizers) and *1/*2 (intermediate metabolizers) genotypes, respectively, reported ≥2 lbs of weight gain. In contrast, the *2/*2 genotype (poor metabolizers) did not report weight gain during this period and demonstrated the highest ESCadj concentrations. CITs did not indicate that these effects were epigenetically mediated. DISCUSSION: These results elucidate functional mechanisms underlying the established associations between CYP2C19 rs4244285 and ESC pharmacokinetics. This mQTL SNP as a marker for antidepressant-related weight gain needs to be further explored.

Epigenetic and biological age acceleration in children with atopic dermatitis.

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease resulting from the complex interplay of genetic and environmental factors, meriting exploration using temporally dynamic biomarkers. DNA methylation-based algorithms have been trained to accurately estimate biological age, and deviation of predicted age from true age (epigenetic age acceleration) has been implicated in several inflammatory diseases, including asthma. Objective: We sought to determine the role of epigenetic and biological aging, telomere length, and epigenetically inferred abundance of 7 inflammatory biomarkers in AD. Methods: We performed DNA methylation-based analyses in a pediatric AD cohort (n = 24, mean ± standard deviation [SD] age 2.56 ± 0.28 years) and age-matched healthy subjects (n = 24, age 2.09 [0.15] years) derived from blood using 5 validated algorithms that assess epigenetic age (Horvath, Skin&Blood) and biological age (PhenoAge, GrimAge), telomere length (TelomereLength), and inflammatory biomarker levels. Results: Epigenetic and biological age, but not telomere length, were accelerated in AD patients for 4 algorithms: Horvath (+0.88 years; 95% confidence interval [CI], 0.33 to 1.4; P = 2.3 × 10-3), Skin&Blood (+0.95 years; 95% CI, 0.67 to 1.2; P = 1.8 × 10-8), PhenoAge (+8.2 years; 95% CI, 3.4 to 13.0; P = 1.3 × 10-3), and GrimAge (+1.8 years 95% CI, 0.22 to 3.3; P = .026). Moreover, patients had increased levels of ß2 microglobulin (+47,584.4 ng/mL; P = .029), plasminogen activation inhibitor 1 (+3,432.9 ng/mL; P = 1.1 × 10-5), and cystatin C (+31,691 ng/mL; P = 4.0 × 10-5), while levels of tissue inhibitor metalloproteinase 1 (-370.7 ng/mL; P = 7.5 × 10-4) were decreased compared to healthy subjects. Conclusion: DNA methylation changes associated with epigenetic and biological aging, and inflammatory proteins appear early in life in pediatric AD and may be relevant clinical biomarkers of pathophysiology.

Circadian oscillations of cytosine modification in humans contribute to epigenetic variability, aging, and complex disease.

BACKGROUND: Maintenance of physiological circadian rhythm plays a crucial role in human health. Numerous studies have shown that disruption of circadian rhythm may increase risk for malignant, psychiatric, metabolic, and other diseases. RESULTS: Extending our recent findings of oscillating cytosine modifications (osc-modCs) in mice, in this study, we show that osc-modCs are also prevalent in human neutrophils. Osc-modCs may play a role in gene regulation, can explain parts of intra- and inter-individual epigenetic variation, and are signatures of aging. Finally, we show that osc-modCs are linked to three complex diseases and provide a new interpretation of cross-sectional epigenome-wide association studies. CONCLUSIONS: Our findings suggest that loss of balance between cytosine methylation and demethylation during the circadian cycle can be a potential mechanism for complex disease. Additional experiments, however, are required to investigate the possible involvement of confounding effects, such as hidden cellular heterogeneity. Circadian rhythmicity, one of the key adaptations of life forms on Earth, may contribute to frailty later in life.

Cytosine modifications exhibit circadian oscillations that are involved in epigenetic diversity and aging.

Circadian rhythmicity governs a remarkable array of fundamental biological functions and is mediated by cyclical transcriptomic and proteomic activities. Epigenetic factors are also involved in this circadian machinery; however, despite extensive efforts, detection and characterization of circadian cytosine modifications at the nucleotide level have remained elusive. In this study, we report that a large proportion of epigenetically variable cytosines show a circadian pattern in their modification status in mice. Importantly, the cytosines with circadian epigenetic oscillations significantly overlap with the cytosines exhibiting age-related changes in their modification status. Our findings suggest that evolutionary advantageous processes such as circadian rhythmicity can also contribute to an organism's deterioration.